This paper presents a novel task, namely the automatic identification of age appropriate ratings of a musical track, or album, based on its lyrics. Details are provided regarding the construction of a dataset of lyrics from 12,242 tracks across 1,798 albums along with age-appropriate ratings obtained from various web resources, along with results from various text classification experiments. The best accuracy of 71.02% for classifying albums by age groups is achieved by combining vector space model and psycholinguistic features.